Schleyer et al. (“A Preliminary analysis of the dental informatics literature”, Adv. Dent Res 17:20-24), indicates a rise in the number of dental informatics papers in journals such as Journal of the American Medical Informatics Association, the Journal of the American Dental Association, and the Journal of Dental Education. Among topics surveyed, imaging, image processing, and computer-aided diagnosis were areas of interest.
Tooth image segmentation is of benefit for dental applications such as computer aided design, diagnosis, and surgery. Various approaches have been proposed in recent years to address tooth segmentation. However, researchers have noted the difficulty of tooth segmentation. For example, researchers Shah et al. describe a method for automating identification of deceased individuals based on dental characteristics in comparing post-mortem images with tooth images in multiple digitized dental records (“Automatic tooth segmentation using active contour without edges”, 2006, Biometrics Symposium). Other methods are described by Krsek et al. in “Teeth and jaw 3D reconstruction in stomatology” (Proceedings of the International Conference on Medical Information Visualisation—BioMedical Visualisation, pp 23-28, 2007); Akhoondali et al. in “Rapid Automatic Segmentation and Visualization of Teeth in CT-Scan Data”, Journal of Applied Sciences, pp 2031-2044, (2009); and Gao et al. in “Tooth Region Separation for Dental CT Images”, Proceedings of the 2008 Third International Conference on Convergence and Hybrid Information Technology, pp 897-901, (2008).
In orthodontia applications, apparatus, system, and methods have been developed to facilitate teeth movement utilizing clear and removable teeth aligners as an alternative to braces. A mold of the patient's bite is initially taken and desired ending positions for the patient's teeth are determined, based on a prescription provided by an orthodontist or dentist. Corrective paths between the initial positions of the teeth and their desired ending positions are then planned. Aligners formed to move the teeth to the various positions along the corrective path are then manufactured.
US 2011/0137626 by Matov et al. describes a method to construct an arch form with the 3-dimensional (3-D) data of patient's teeth and facial axis points for the teeth. However, the Matov et al. method does not provide the ability to visualize maneuvering the teeth individually and digitally for treatment planning. With this and other methods, the digital data obtained from the Cone-Beam Computed Tomography (CBCT) dental volume image is not associated with desired teeth movement or a corresponding treatment strategy. This limits the usefulness of the volume image data.
Thus, there is a need for a system and method for automatically segmenting teeth from CBCT data, with tools for automatically analyzing tooth alignment and allowing a user to manipulate teeth digitally.